How to choose evaluation functions for features, when network effects are in place (multi-agent systems)?
In a sense it seems like I am thinking some kind of "Deep Agent-Based Modeling", where it is okay to have network effects on the lowest layer (which would only evaluate the matching of the generated artifacts and their own preferences); the co-operation problem should be solved by a "Coach" layer, which would attempt to prevent situations, where some agents can not play well together.

The evaluation function of the "Coach" layer should be such, that it minimizes the amount of negotiation actions (energy efficient co-operation) required per artifact list generated and also minimizes the signaling distance regarding diversity (less popular artifacts / unorthodox solutions). The "Coach" layer should also be able to reorganize the lists contained by the Agents. The signaling distance can be easily evaluated in my use case, since the dataset has easily available popularity ranking per list artifact list item; the shorter the distance from popular artifact list to the least popular artifacts is, the better.

In practice this means, that I actually want to build composable Agents, which have lists of items (or other Agents), action space for generating artifacts from those items, evaluation functions and costs of specific actions, aggregateable popularity rank (which helps to evaluate delegation). All Agents would have generic default action space, which would help in solving the signaling problem; if the diameter of the co-operation network is too long (not within the scale-free network topology), the system should attempt to create a new layer or reorganize the existing layers (or do both).

All this might be computationally very expensive; however we tested a theory about building a "multi-dimensional" merge-sort algorithm by using entanglement / super dense encoding from quantum information theory and it would seem like it could work and be able to create a hash map, which would allow the Agents to reshape the scale-free network efficiently.

I might build some kind of demo out of this, since all this seems really interesting to me and complements nicely my past hobby projects.

I will not accept this answer until I get some verification, that this is a good answer. However, I will post this in hopes, that someone has already done similar work, gets inspired and can provide a better answer. This answer will probably be edited later, when I get to a more formal level with this.